visualize_features.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5d10f202-f566-40fc-a6f1-d40162aad7bc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use(\"science.mplstyle\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "628ec0e4-4cca-4760-8ff8-1fdeb2b59c03",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from madminer import SampleAugmenter, sampling\n",
    "\n",
    "import yaml\n",
    "with open(\"workflow.yaml\", \"r\") as file:\n",
    "    workflow = yaml.safe_load(file)\n",
    "\n",
    "data_input_dir = workflow[\"sampling\"][\"input_dir\"]\n",
    "sig_precode = \"delphes_s\" \n",
    "bkg_precode = \"delphes_b0\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "cab5df9b-dd2e-42a7-9a92-687f1e893d79",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(44120, 20)\n"
     ]
    }
   ],
   "source": [
    "sampler_sig = SampleAugmenter(f'{data_input_dir}/{sig_precode}_shuffled.h5')\n",
    "\n",
    "x_sm = sampler_sig.sample_test(\n",
    "        theta=sampling.benchmark(\"sm\"),\n",
    "        n_samples=36000,\n",
    "        sample_only_from_closest_benchmark=True,\n",
    "        validation_split = 0.0,\n",
    "        test_split = 0.5)[0]\n",
    "\n",
    "x_alt_1 = sampler_sig.sample_test(\n",
    "        theta=sampling.morphing_point((5, 0, 0)),\n",
    "        n_samples=50000,\n",
    "        sample_only_from_closest_benchmark=True,\n",
    "        validation_split = 0.0,\n",
    "        test_split = 0.5)[0]\n",
    "\n",
    "\n",
    "x_alt_2 = sampler_sig.sample_test(\n",
    "        theta=sampling.morphing_point((-5, 0, 0)),\n",
    "        n_samples=50000,\n",
    "        sample_only_from_closest_benchmark=True,\n",
    "        validation_split = 0.0,\n",
    "        test_split = 0.5)[0]\n",
    "\n",
    "x_alt_3 = sampler_sig.sample_test(\n",
    "        theta=sampling.morphing_point((3.79, 0.55, 2.19)),\n",
    "        n_samples=50000,\n",
    "        sample_only_from_closest_benchmark=True,\n",
    "        validation_split = 0.0,\n",
    "        test_split = 0.5)[0]\n",
    "    \n",
    "sampler_bkg = SampleAugmenter(f'{data_input_dir}/{bkg_precode}_shuffled.h5')\n",
    "\n",
    "\n",
    "x_bkg = sampler_bkg.sample_test(\n",
    "        theta=sampling.benchmark(\"sm\"),\n",
    "        n_samples=8120,\n",
    "        sample_only_from_closest_benchmark=True,\n",
    "        validation_split = 0.0,\n",
    "        test_split = 0.5)[0]\n",
    "    \n",
    "x_SM_sb = np.vstack((x_bkg, x_sm))\n",
    "\n",
    "sets = [x_sm, x_alt_1, x_alt_2, x_bkg]\n",
    "names = [\"$x$ ~ SM\", \"$x$ ~ ($c_{\\phi}$ = 5)\", \"$x$ ~ ($c_{\\phi}$ = -5)\", \"$x$ ~ bkg\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "86af3614-fd9a-4f07-8bfa-7f25046df8a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "nb = 35\n",
    "\n",
    "feature_labels = {\n",
    "            15:\"$m_\\mathrm{tot}$ [GeV]\",\n",
    "            16:\"$p_{T_{\\gamma\\gamma}}$ [GeV]\",\n",
    "            17:\"$p_{T_{bb}}$ [GeV]\",\n",
    "            10:\"$\\Delta R_{\\gamma\\gamma}$\",\n",
    "            9:\"$\\Delta R_{bb}$\",\n",
    "            11:\"$\\Delta R_{b_0 \\gamma_0}$\",\n",
    "            12:\"$\\Delta R_{b_0 \\gamma_1}$\",\n",
    "            13:\"$\\Delta R_{b_1 \\gamma_0}$\",\n",
    "            14:\"$\\Delta R_{b_1 \\gamma_1}$\",\n",
    "    }\n",
    "\n",
    "\n",
    "feature_ranges = {\n",
    "            15:[250, 1650],\n",
    "            16:[0, 800],\n",
    "            17:[0, 800],\n",
    "            10:[0, 2.5],\n",
    "            9:[0, 3],\n",
    "            11:[0, 4],\n",
    "            12:[0, 4],\n",
    "            13:[0, 4],\n",
    "            14:[0, 4],\n",
    "         }\n",
    "\n",
    " \n",
    "kwargs_dict = {\n",
    "               \"$x$ ~ SM\":{\"lw\":4, \"color\":\"navy\"}, # nacy\n",
    "    \"$x$ ~ ($c_{\\phi}$ = 5)\":{ \"lw\":3, \"color\":\"#4641D9\",  \"linestyle\":(0, (1, 1))}, #41D9B3\n",
    "         \"$x$ ~ ($c_{\\phi}$ = -5)\":{ \"lw\":3, \"color\":\"dodgerblue\", \"linestyle\":\"dashdot\"},\n",
    "            \"$x$ ~ bkg\":{\"histtype\":\"stepfilled\", \"lw\":0, \"color\":\"black\", \"density\":True, \"alpha\":0.3}\n",
    "              }\n",
    "    \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def plot_features(samples, sample_labels, feats_to_plot, cuts = None, name = \"\" ):\n",
    "    \n",
    "    num_feats = len(feats_to_plot)\n",
    "\n",
    "    fig, ax = plt.subplots(1, num_feats, figsize = (4*num_feats, 4), dpi = 300)\n",
    "\n",
    "    for i, f in enumerate(feats_to_plot):\n",
    "        \n",
    "        for j, samp in enumerate(samples):\n",
    "            \n",
    "            if sample_labels[j] !=  \"$x$ ~ bkg\":\n",
    "            \n",
    "                loc_bins = np.linspace(feature_ranges[f][0], feature_ranges[f][1], nb)\n",
    "                loc_centers = 0.5*(loc_bins[1:]+loc_bins[:-1])\n",
    "                loc_vals, _ = np.histogram(samp[:,f], bins = loc_bins, density = True)\n",
    "\n",
    "                ax[i].step(loc_centers, loc_vals, label = sample_labels[j], **kwargs_dict[sample_labels[j]])\n",
    "            else:\n",
    "                ax[i].hist(samp[:,f], bins = loc_bins, label = sample_labels[j], **kwargs_dict[sample_labels[j]])\n",
    "            \n",
    "            \n",
    "            if cuts is not None:\n",
    "                for k in cuts[i]:\n",
    "                    ax[i].axvline(k, color = \"black\", linestyle = \"dashed\", lw = 3)\n",
    "            \n",
    "        ax[i].set_xlabel(feature_labels[f])\n",
    "\n",
    "        ax[i].set_yticks([])\n",
    "\n",
    "        if i > 0:\n",
    "            pass\n",
    "        else:   \n",
    "            ax[0].legend(fontsize = 13.5)\n",
    "            ax[0].set_ylabel(\"Density\")\n",
    "\n",
    "    plt.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "    plt.savefig(f\"plots/{name}_features.pdf\", dpi = 300)\n",
    "    plt.show()\n",
    "    plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "ff656af5-3d58-4bcd-9a52-329dfda4531c",
   "metadata": {},
   "outputs": [
    {
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bb/1+2HB5rze8i2RJcrkc+sazRaquyQr7XKOqq4u1d+9j2rDhTW3d2mpZO/HK7w8YLhtvO8F+fJFUlhfeOR0DUkmO8fJHz4ZXPwAgfl2c69Gpmwvlmz39jbiLkk53Gqy0qFieqCMDAADXqqur1MaNe+wOwzZbt7aqsbFTNTXFUdf1arP0WpjjwD+9N+pmAQAAACBmurv9+vaLPfL7ph/AfO7Fkhnrmjh2/NYBv4q8iyVJgWBAg0P9GhjoU++ZDgUCxsdYp+N0OlUwr0Q5OXnKzsqV0+GcsuyBg78Kq+4i7+Ir8UvmPYennvplXCWguiyapM43e6U3HpJ2HA9tUnT0rOQfNyeu5tPSgM+cugAAAAAAsEKRd7FKi8v0j68an68fDwuEAQAAACCVZGQ4VVJibAXTqVOjGhuLfAHw2FhQHR0jEZ8fMqK+s4e18qbbdK4vTef6oqzOYnnzRtXRbrxfnJM7Flb9Lc25YZUfD6Ru3pORsdAmUvGwhh0koYKFovmgipUFC1I7IyAAhGvJjdanXPD7g/rm012WJ6KqqipQQ8ODamzs1JYtR9XSckZtbX1hJWiaTHPzaZMitE5z82lVVW0K6xz3/AKNfPwOBefOtSgq48JJKCVJf/Er6bGVxsubNbkYAGCvi3M9ev/WEskZXzfhLly4oIaGBrvDAAAg7tTUFGvduiXatu2Y3aHYZsuWo6YkoTo5IO0zmmATAAAAABKQ1+vSH98zV998ukt+f/Tzky6PHX/rL9/TP7/pv/L4vLwFV/4dCI7L7x+46rzT535vuI3m5tNaWrFKJcVLoo53KpmeLOXNLbzqscvPYXCoX+8c2aeBCx/M9G1r65tx3Djex7+jSersSZfqbgwdZnrgNfrlAAAAAIDYCTeJtSSVLbpJWZnz1XXSgoAAAAAAIEWUe86EVb7Tl6uLAZfh8kuWzNJX/naZobKPP95sQhKp6J3tO6WD7+zWyptuU1pamil1pqUFNG/+qHq6M02p77KCQvt/X6lmqvV0+weLdfzch2McDaZCEiqktIULrU+mAgDJ5NbbsvVyqVsd7dZu22kkEdXO7f3atWNg0p9NZbKdbmtqik1Z4HlZY2OnVq/+e9Pqs0r4k4VPS3tbNGv5UrlLiuRaUCBH+gedwPy8TH3oQ3OVleUOO5apJuCeDO/lndLomPS5rdKy+ebUBwCIf+MO6dTNhXGXgAoAAEyvvv5O7dnTrv7+UbtDsUVLS3iD0QAAJKKyDV+W3zvHcHlX93kd/9bfWBcQACBhVddk6RvPFpmWiEqSiotnS5p8O1anI00Z7qs37Dl8+POG6245clFffrwjrHiWzTDA2dbWJ5/P2A472Vm5qvlwrfa//Uv1D5yVJPl843GfZMoIs5I6AwAQqdnZc+SfudhV5XstiwYAAAAAYCfGQwEASA2fyD2uu/Obwzrnr7s+qraReYbLd/py9dddHzVW+P4VKhgNTPnj4Ni4/N298rV3afjQEWnM2DhzJMxMRJWWFtCnPt2p7lOZpiehKisf1IG8UZ3ryzC1XoSvfTTX7hAwAUmokNJqanhDAoBwuN1Ofe2pQj3xxQ4Fpu6PmGKmRFQ93X4darpobRARqKkp1rp1S7Rt2zG7QzHf2LiG33pHw2+9c92PeiV15WZo166HVV0d3gTfkTHpUy9Lx89d/fjCnChivcbouPR2t3n1TeaB165/zJUmVeRLywukteWh3XQBANYb+5BHvnFuAgIAkGiqqgq0a9fDqq3dnJKJqF5//YiqqjZFVYfL5ZTnE7dJN1SZFBUAAAAA2Gfn9n71dE+f0qGsPEMtR+J7h1KfL6Dn63vCPm+mJFdVVZvCSiLldDpVVbla+w5sV8DqAf8YIqkzAAAAAADWe/zx6xdXp6c75PVmaOHCDK1ePUcVFZNvPg0AAAAAyaY047zlbVwMuAwnrXKUSJ4ZymRWlkmS/N2ndfbln8vX3hVRXEXexcr0zNz/uzB4TnNyjSfdutblBFQ3LBpW9ylzE1BJUnp6UHes6dbrPy1VMOgwvf5oHDmcoyPN4eVBufu+8DbFiienfCYuJkfUWAaPlFVdncMNTgCIQOXSTL34nRI9X9+jjnafpW3NlIgqXtXX36k9e9pTbsFsf/+oams3a+/ex1RVVWD4PE+69MIa6Z5XpHFzNim2xb7OyR/f3R76Wr5feqFWWumNXUwAkIoOH+7VK7tPKOMPp98hHgAAxKfq6mLt3fuYNmx4U1u3ttodTsyFs3h4KrkLTiv3BhOCAQAAAACb7doxEJcbE4Vrz+5By8fWjcrOylXBvBJ1975vdyimaWvrszsEAAAAAACSXkfH5EnA33svdO/m1Vd7tGpVjh59tFilpeYvDgYAAACAeOF1XdCKWd12hxExl3e+Cr/8WfV8+/vyvT/FothpFHkXK29uoQWRfSA9LXglAZWVvAtGdM8D7Xpzp1fn+jIsbSscAwMudZ2cFdM2GxoaYtreRGNxlgQs1ZGECikpKytNjzxSbHcYAJJQLC6y1q9fb3kbM6lcmqlNL5Vq7+5BtbaO6sS74SdbKvS6tHyFsQGmn71+TiWlbnm9rrDbsUNVVYF27XpYtbWbUzIR1YYNb6qh4cGwzrvZK71+v/TkTun4OYuCs1lbn1T3UykjLfR8zeJKkyrypeUF0tryUFIvAEhlTz31SwVKVtsdxnWCY+N2hwAAQMKoqipQQ8ODamzs1JYtR9XSckZtbX3y+wNR1WtGgicAAFKFzxfQnt2DOnZ0RCfe82lsbOYdBJ57sSQGkQEAkHiOHR2Ry+VQWXmGWo5MvmAzlnJm5yVVEqpo7xcAAAAAAABzHDgwoCNHhvTMM+VasiRxNqAGAAAAAKOcCugz8w/K5UzsMUpHmlP5D9Xp1HPfk8Jc7xQIWv/cP35Ht3JyxwyXT3POPLdtKt4FI3rgT9/Xu23Z6u3x6OyZDI0HSIqE1MUSdaScrKw0PfNMOZn1ASBKbrdTt9+Ro9vviOz8NWtztWZtrrlBRWnn9n7t2jEQ1jlTLaqpri7W3r2PacOGN7V1a6sZ4SWMrVtb1djYqZqa8BI+3uyV3nhI2nFcOtQjLZ5jTXx2Gx2X9oWfIHpau9tDX8v3Sy/USitNTHIFAInkd787qW3bjqngC39odyjX8Z/qtTsEAAASTk1Ncdh9y+k0NnZq9eq/N60+AACSVcuRi3q+vkcd7T67QwEApLj0dOsndnZ3+y3fDKmr069vPFukluaLliSh8niyNDIyZLh8dnZ8jdNHq7n5tKqqNkVVh8vlVFlZnior81VXV2nq/QgAAAAAAFLJ0NC4vv71NtXXV7BuCwAAAEBS8bou6DPzD2qR57zdoZjCVThfs5Yv1fBb74R13uBQv+blLbAoqpCJCahaW4d0qMktad6U5Q82dWnnr5pNaTs93SGvN0MLF2Zo9eo5qqiILMnyF544ako88e7I4RwdaQ5vDsLd93VYFA3MQBIqWG7Vyk8ob26h4fJ953p04OCvLImlujpHjzxSzI1MAMCkerr9OtR00bT6qqoK1NDwoBobO7Vly1G1tJxRW1tf1DuxNjefNilC62zZcjSiibmedKnuxtCB8LX1SXe/Ir1+fyipFwCkmi1b4vcGna+jy+4QAABICDu396un23/d4z09Y1Mmjt7xqwpDddfUFGvduiV6+/djKvIuDiuucO9ZF3kXX9dGIBjQ4FC/Bgb61HumQ4FAYu+CBABITi1HLuqJL3Yoko+pickfLly4cNXPTp0ajTY0ADBVQ0OD5W2sX7/e8jaS3aLFbr31+2FL2/i77/Tqrro5qq6JbOKoEf/piwXyel1qaTZvLHqiZRXVev+k8fvjTofTkjjsZMYYelNTjyRp48Y9Wrduierr71RVVUHU9QIAkt/c7f8a9jzpyRR6XVq+gvnNAAAg8Q0NjeuHP+zU00+X2x0KAAAAAMyo3HNmyp+lO4Iqcg+oNOO8VszqlsuZXHN/3SVFYSehGhjosyiaq7W3X9QPftCpAwcGVLboJpVNM/W7s+u0unvN2xDqvfdCY/uvvtqjVaty9Oij5CeZysCAS10nZ9kdBkxEEirErfR0hxYsyDCljoULPaqpyY040yAAANGoqSk2dafUqqpNcZ+IqqVl6o43rDUelJ7cKb3xUCipFwCkkpaWs3aHMCl/92kNHzpidxgAACSEXTsGTE0Qfa36+jt1/72/DWtBUCQyPVmTtnF555/BoX69c2SfBi7EZiAWAAAjfL6A/vKZzogSUEmJsYECACCxLLnRY3kbRcUuffPpLn3j2SLL2vB6XZbVLUlOp1Mrb7pNFwbPWdpOKtm27Zj27GnXrl0Pq7ravLF+AACms2ZtrtasDW+38FQVi6SyAAAgOvv3D6i1dYh1XAAAAADi3leKfhuTdtIdwZi0Ew7XgvA35ek906HBoX5lZ1l3P/vYsSF9/ettGhoan7Hs4FC/es90WBbLgQMDOnJkSM88U64lSxKzj3vkcI6ONIf3et19n3W/U8Q3lqUjbi1YkKG//dtldocBAHGHXXnhcsX/zrRtbfGziPan91rfRseA9W2E4/g5acdxqe5GuyMBgNg6fjx+Pn8uC44HdPbln0tjoRuf6ekOewMCACAG4nm39qqqAj388HL98y/9tsaRnZWrmg/Xav/bv1T/QHwm0pxKx4D0F7+SRsesa8OVJlXkS8sLpLXlJFkGgFj50Q861NuTXLv1AQAS2623ZevlUrc62n2WtbHkRo/8/vP65tNdKiuPbrO8WJs4bpyWlqY5ufNsjCb59PePqrZ2s/bufUxVVeFPvjbbA6/NXIb+NAAAAAAgnjQ29pOECgAAAAAuWeAeUMvF+XaHcRVHelrY5wQCAR1u+Z2qb75TTqf5a53b2y8aTkAVCAT0zpF9CkS666JBQ0Pj+vrX21RfX6HS0vicIz+dgQGXuk7OsjsM06SPjSv74vWbXs+bP6J5+cbnTezc3i9JbBByDaYZAAAAJJiysjw1NfXYHca0mpp6VFW1Kao6XC6nysryVFmZr7q6StXUxO8Os3/xK7sjuN6hHpJQAUg9fn98LZT1d5/W2Zd/Ll9715XHFixIrEVMAABEIt53ay8umi3J/uSVTqdTVZWrte/AdssHP81UkiM9tlL63FZpdObx3Yjtbg99Ld8vvVArrfRa1xYAQDp8uFff/pt3tKBwiaXtBONvQz8AQBxzu5362lOFeuKLHbKq2zQx0VXLkRFrGrFIIowbJ7r+/lHddNPfadky45PBh++qk4rMH9ve12msHP1pAAAAAEC8OHkyse61AAAAAICVSjP67Q7BNP0DZ7X/7V+qqnK1srPCnzP++OPNU/6so8NYX3JwqF/vHNmngQuxmRM+NDSuH/6wU08/XR6T9jA11/lRefd2Xff4F544qvXr1xuuZ/MP7N3UOl6RhAoAACDBVFbm2x2CIc3Np6Ou4/Kk6Y0b92jduiWqr78zLnaZvVYgDhdOHT1rdwQAkDgCF0fk6+w2pa7g2Lj8p3rl6+jS8KEj0tjVmRkWLvSY0g4AAIgtI4tNI+kHZ2flqmBeibp7348kLNt8fJH00l3WJ6KSpLY+6e5XpNfvl25m4SwAWOapp34pl8v6jQCGL16QW3MMlydpFQCgcmmmXvxOiZ6v71FHu8/0+mOR6MoqiTJunAzC6vM3/72hYlaPf9OfBgAAAIDklp7usDuEGZ06NWp3CAAAAAAQN1bOOqXtrgvq8c+2O5SwFHzhkSl/dlySy+VRWlq60tLS5XBInrYeZbb1Tlun0URTkpRVs0K+W2/RcbdHGg8o0HtOo++fVPfBvQr4YptEaP/+AbW2DqmiIium7QKxRBIqAAAAC+zc3q+ebuMdmEKvS2vWGsv4W1dXqY0b90QaWsLatu2Ytm07JsnY4t+ZuFxOlZXlqbIyX3V1laqpiXyBVUX+BzvKxovd7dIDr5lTlyst9ByXF0hryyUPvQgAScbX2a3e7/4wJm3V1ISf4R8AANjv8OHPz1jmnnte0T/+45Gw686ZnWdqEqqxvvMaaTsx5c9nzXJd91hV1S8M1z+xP/3kv1mhF47NszwR1XhQenKn9MZD9EkBwAq/+91Jbdt2TKtWlljeViAQ3ofG+PiYRZEAABJJ5dJMbXqpVHt3D6q1dVQn3h3V2Jh5mQovJ7r68uMdptUZiYwMh26sNL6RQaKMG880tmvG5kaJaNu2Y9qzp127dj2s6mprkoHSnwYAAACA5OX1Zui99y5GdO7FkSH1nesxOaLrmXn/BgAAAAASncsZ0MPzD+qvuj6mgJyWtxf0j+n0//qJRlqOR1WPp3zRzG1JujzL68zBg+o/+H+janOi9Lw5cpR6dWW1dnGe0m8u08J/+0cK+PzytXea1pYkBcfG5e/ula+9S8OHjkhjV893a2zsJwkVkhpTCwAAACywa8eADjUZH9hbviLTcBKqmppi/T+fvEWne2ZN+vNAMKDBoX4NDPSp90yHAom2Za8BZk1EbmoKDaBu3Lgnqp1ml1uzOW3U9pnYf76cZKt8v/RCrbSS3XIBIGzV1TncaASQkBoaGixvY/369Za3gcSQCLu1TqWyMl+S5PGE93mfnW1uksqhxiYNNTaZWue1LventXGP/s2/+zfqXPVx+QPWvnbHz0k7jkt1N1raDACkpC1bjtodwpRIQgUAuMztdur2O3J0+x3W1F+5NFMN28stS3QlhTYmWr4i88r36ekOLfpQhioqMvSx27Lldoc30bimpljr1i1Rj7lzak1z110Vamh4cMZyVVWbUjYRVX//qGprN2vv3sciGqc2gv40AAAAACSnhQszIj63q/s9dXW/Z7h8kXexyhbdZLj8xZGhsOoHAAAAgFSxyHNeXy3aq82nV6rHP9vSthyudM3/7J+YkogqXjndLkNJssKVWVkmSfJ3n9bZl38uX3vXlZ+dPDlienswx+OPN2vDBuObj+VkfUiS9K3n3p2yTFnZXG3ZMvO8h2RCEioAAHCdRFhgfO0E3VRzxx2V2vlPo1P+fF7eAknS4FC/3jmyTwMX+mIVWsKKZqfZteWSdlgTV7xp65PufkV6/X7pZhJRAYBhWVlpeuQRa3YyBwAgmSxa7NZbvx+2O4yI1NVVauPGPVpWUa30dJfh85wO63czstJvfvQb5R/u1Zx/d7/8QWsTUX1pu/Tyv5pTlytNqsgPJZZeWy55GDEDkMJaWs5KCi06OXe+d9qy+XkLNCd3XsRtDTUe1GjbCUnS3DkFmjuncMqyPv+I3n/nQMRtAQAQLqsTXa1Zm2t4YyKj6uvv1J89eizs84q8i1XkXRzWOQcO/spw2dzcDH3rW8Z+kS5XYveLo9XfP6oNG940lLArUod6SEIFAFYy0p+e6OLIkIXRAACAVLF69Ry9+mpPTNoq8i5W3typ7+dfq+9cD0moAKSskd8flit/rvHyZ89ZGA0AAIhHizzntaH4N2oa9qp9dI66fDkaM3H+7ehIQN09o7pwYVySNPuPbpG/94zG+/pNayNVuLzzVfjlz6rn29+X7/3Q7lCnTk29rttO/oBTB4cXqH00V6eu+Zu6MNelgY9NPrf9hr0nYxXilIaH0qW06Ovp6BiRZDxJWNmi0L2O4ydSc9OsqTClHgAAJCQrJugmkoL5WZJm7qxkZ+Wq5sO12v/2L9U/cNb6wBJcpDvNetKljDRpdNzC4OLIeFB6cqf0xkMs0gUAI7Ky0vTMM+UqLU3dBJoArBOLJMJALC250WN3CBGrqSnWunVL1NPpjCo5R7yY/x8/c2UnHyP8QQuDmWBfp3l17W4PfS3fL71QK60k2TKAFHX8eGgTg5kWhOTnLdCi0mVRtTXU2HTl3/MW3aT5iye/wRgIBNT41i4NXtpgIT3d2kSHAGCFRNj4B4mvqqpA397kV23tZvX3G5/sWrboprAWj4YjNzdDu3Y9bHi8tawsT01NsVk0G6+2bm1VY2Onamqs2cziKFMFAMBSJFgAAAB2qKjI0qpVOTpwYGDSn6fl5SrvvrvkcEU/0fdc9hxdSHdf97gjEFTGgE+e8yOafWpQzkCMBo0BII517vql3SEAAIAE4HIGtCq7S6uyu6xp4ENSa+uQGhv7dfLkiE7l+jSWlbhztO3kSHMq/6E6nXrue9LYuN5776Ief7zZ0jZzZ5cqN8d4H3s0L1tf+f0tcuTnT17ALSmOp7YPDqZJqZsuIO6wZBwAACDJOZ1OVVWu1r4D2xUIBOwOJ+5FutNs6xekt7tDyZmOp8BmFMfPSTuOs2MugPg0O3uO/GGWN74vbXiqq3P0yCPFJKACAMCgW2/L1sulbnW0++wOJSL19Xfqzx49ZncYpvB394aVhCqRtfVJd78ivX6/dDOJqACkIL9/5vvG+XkLtPKm25SWZsKWYzMYHOrXO0f2aeBSAipJWrAgw/J2AQBIVNXVxdq79zFt2PCmtm5ttTWWu+6q0Le+dUdYG/5UVk4xETbFbNly1LIkVP4U2UwJABAf2EAFAIDYefTRYr3rKdN4ds6kP3dmepSxaGHU7fgvHZMZLsiSJJ29MKoFb/Uo8/xI1O0BAAAAAKJXUZGlioqsqOv5wrsmBJPgXIXzNWv5Ug2/9Y4kqaPD2r5vh1olGRv7d99QrML7HpMjzWlqDDMl2kpPd8jrzdC8udFluGpvv6ihoVEpd3bEdcBcJKECAABIAdlZubp55TJdHDG2g2xz82mLI4pvW7e2yuH4ppYtmx/2ucG0NGUsWqzA/AIF8/PlycrQrFkuzZs3SzmzI18ota8z4lMtc6iHJFQAkovbnaby8ryrHrtw4UJYdaSnO7RgQYYWLvSopibXlBu2AACkErfbqa89VagnvtihRMyjXFVVoOUrBnTi3QQM/hq+dot2V4pT48FQYuk3HpI8jJ4BgJSeplnLl8pdWiRP0QLNmj1HJxzTn1JQ9chV3w81HtRQY9OU5S+ODKnvXOiedSAY0OBgvwYu9Kn3TMd1GyosXMhOfAAATKeqqkANDQ+qsbFTW7YcVUvLGbW19U2ZbDInK/x715ONnbpcTpWX56mycp4+/ekbI0qiVFdXqY0b94R9XrJpaTljdwgAAAAAgARTWpqpG+9ZrU6H8WTQVvHNztD7t5Xohj0dUgps5gsAAAAAsE5aXq7G+/rtDuMq7pKiK0mo4kZ6mvIfqjM9AZVkLNHWe+9dVNmiQZUtjrydH/ygU/7bxmT+M0CkmEYPAABwSaHXpeUrMm1p2+WeYfWOCf7Dn/0b/f/+k7GkSitX/g81NRlLWJXMIk7G9a/dkz68bt0S1dffGdbOv5d95mfS7vbIwrHK0bN2RwAA5iovz9Phw5+/6jF2aQUAIPYql2bqxe+U6Pn6HnW0++wOJ2yhBMQXIzq3yLtYRd7wRuIOHPxVRG3NZPjQEfl7TstVGH6C5kR1/Jy04zgJlwHAfUOx8h+qu+ozYMzAeR7Nuer70bYT05bv6n5PXd3vGYqppibXUDkAAFJdTU2xoURQm39wRj/+UV9YdV97/9wsNTXFWrduibZtO2ZJ/YmirS281+Oym73SH90wfZmFORFVDQAAAABIAJmZTmnmdaGx4XTo1M2Fyn0/ziY8AwAAAAASyty7/x8N7tmvkZbjdodyhWuB/QmgrzVr+VLb53lP3IgyLc2hRYsylTkrzdC5R48O6cCBARXeMqIMK4NEWEhCBct1db+nc+d7DZe/ODJkYTQAAExtzdpcrVlrzkKW9PTwkkp96YlCU9qdzol3Ryd9fOf2fu3aMXDVYwsKauRaOfVnslULXJPdtm3Hrkyenmyn4OmM3vKH0vKVFkQVOf+4+XU+8Fp45e9dJt23zPw4AAAAANircmmmNr1Uqr27B9XaOqoT745qbCxoSt12JqGeTFaW+0ofMSerQDnZ1t8jMGRsXGdf/oUKv/SYJTvkxKtDPSShApDa3DcUx917f3V1jioqsuwOAwAATGOyMeeZPPdiyZV/19ffqT172tXfPyBjUVgAAKP5SURBVPmYthRfiZut4PcHIjqv+bT0ldXSxxdF1u6rzdJrzcbLu9KkinxpeYG0tlzyMAMVAAAAADCBb3aGRkvnSb+3OxIAAAAAQKIaO9On+Z/9E53+Xz+xO5QrHOnGEivFkru0yO4QrtuI8neX7geUlHimPOfNX4e+dnSEsmqbs0LAGhcuXFBDQ8OV79evX29jNLHBFABYzujutQCA1DLxossqdl7MLVrs1lu/HzZc3ut1WRhNyFSLdXu6/TrUdPGaR7OVNzfb8phSWXPz6bDKz/Ic17w4S0K1rzOUNOqn95pbZzhuWWhe2wAAALBPsvcRERm326nb78jR7XeYW6+ZSajNUF1dpOdeXC1J2vyDM/rxj/psjugDvvc71fPt7yv/oTrbd8qJlaNn7Y4AAGyUnqb8h+riKgFVVlaaHnmk2O4wAADADCYfczauqqpAu3Y9rNrazVMmosr0ZClvbpwkbo4jo+PS57ZKL90VWSKqkwPhj9Hubg99Ld8vvVArrfSG3y4AAAAAIHn585mDDgAAAACInK+9S46Pp2v+Z/9Evs5uu8OJWy5vQdR19J3rMSGS611OMIXEQxIqAAAACyy5ceosrUAkhg8dkb/ndNwt+g13QjIAAAAAJLvnXiyxO4TrFHkXq8i7OKxzDhz8laRQIqpTz31Ps5YvlbukSK4FBabt5uMpX2RKPWba3R5KuGyUmYmZAcBus5Yvjav7j1lZaXrmmXKVlmbaHQoAxC2SOiOZVFcXa+/ex7Rhw5vaurU1pm1H0282S3PzaVVVbZry58676qb8mV/SY98dV9a+3aoodKmyMl91dZWqqbE2mWdbn3T3K9Lr90s3k4gKAAAAAGyR7ph8k2I7jc3NsjsEAAAAAEACm7iWNmPRQrvDiVtmzOc2e9w7FsbGfKYkz7o4MmRCNMmHJFQAAAAWuPW2bL1c6lZHu8/uUJAsxsZ19uVfqPBLj8mR5rQ7GkwwMiZtb5MO9UqtZyX/uHVtudKkinxpeYG0tlzy0KMDAAAAYECmJ0t5cwsjr2BsXMNvvaPht94xLyhJsz58k+b9u3tMrdMMJFwGkKrcpUV2h3BFdXWOHnmkmARUAACkmKqqAjU0PKjGxk5t2XJULS1n1NbWJ78/oJys8BewLlv2QYLN5ubTU5aLut9skuliVPPfG6rjcs9948Y9Vx6b+Hu41uhHqqWPVBuqezLjQenJndIbDzF2CQAAAAB2WOAeUMvF+NlgQpKU5rA7AgAAAABAImMtrSFDjQc12nZixnKeyvKkSuZ1YfC8jpuQPKur+z0Tokk+DPsDAABYwO126mtPFeqJL3YoELA7mtiLh51ik5Hv/U71fPv7yn+oTq7COBswTlFvd4cmVR8/F7s2d7eHvpbvl16olVayqzAAAIAhDQ0Nlrexfv16y9sAksnEnYpS3QOvhVf+3mXSfcusiQVA6nJ5C0ytLycnXTklHkNl09MdWrAgQwsXelRTk6uKCnZJB4BUQX8dk6mpKVZNTfFVj23+wRn9+Ed9YdVz+PDnJ/y7Vx/72PfV3z9qSoyJZLrkVrmlQ8qNsv7j56Qb/1a6pXjmsjNhUx4AAAAACE9pRr/dIQAAElQs7s8DAIDEV+45c+XfoyMBvfvuRY0HglOWH+s7b0q7l9fSep/4M1PqS0ZDjU0zlvFUlinnjltjEA2SBUP0AAAAFqlcmqkXv1Oi5+t71NHuszucmIqXnWKTke/9Tp167nuatXyp3CVFci0okCM9zZS6PeWLTKknUbzaLL3WHPn5b3dLo+PmxROutj7p7lek1++XbiYRFQAAAIBExE5FV+zrDK/8LcmzIRGAOGLWfcbLPvWp+Vr3GTLmAUCiYxEKkkVVVYF27XpYtbWbbUlE5fFkaVlFtZzO6fu/4W7eNHGDqEAwoMGhfg0M9Kn3TIcCMd4xK9y+7VQub8pT/Bu/Nn3axaY8AAAAADCNlbNOabvrgnr8s+0OBQAAAACQhL5S9Nurvj82PqSvf71NQ0PWL6z0vd+p9q/9t2nX0qY5HVq0OFOZmcbmIbe3j2hgYEzuYq+cmcY2WExUnsoyzf/sn8jhMj+tUFpervLuu8uUut3FDAjHE5JQAQAAWKhyaaY2vVSqvbsH1do6qhPvjmpsbOosv0YVel1aviLzusddboe+9EShvF5X1G3Eq4mTaI2KZqKuVW1EZWxcw2+9o+G33jG12oIvPBJRIqqqqk3mBfG5z89cZoK/3bRff//Z/YbKulxOlZXlqbIyX3V1lToZKDZtIrRdxoPSkzulNx5iF2AAAAAAienyTkX5D9XJVTjf7nDCNl2f+Np+aE1NcQwjM2ayBM0DF0Z15sywhof9GhkalePsWTlPn1b6iXflGDd/0kAi/J4AAAAAJIfq6mLt3fuYNmx4U1u3tsa07ZGRIb1/8qhW3nSb0tLMS/557QZR8/IWSJIGh/r1zpF9GrjQZ1pbsdZ50aW6fwjor1af1z1/mGd3OAAAAAAQl1zOgB6ef1B/1fUxBZTaG/8AAAAAAKy3ZEmW6usr9MMfdmr//gHrG5xmLW11dY4eeaRYpaXXr7WeyuY3O/Xqqz1hr6V1F3tV8IVHDJc321DjQQ01Nhkub2UCKkka7+vXhf+7z9I2YA9eTQAAkLRisSvv+vXrZyzjdjt1+x05uv0O89pdszZXa9bmmldhmFasKJTfP/WuqTlZWZa1fe0k2kRtIx4FxyJbSNrcfNq0GErDLH/m9JD6w2i/qalHkrRx4x6t+uLdUtkfhNli/Dl+TtpxXKq70e5IAAAAACAyvvc7deq57027U1GkIkm2HI6Z+sQT+6GXLVs2SbKtCJMyR5vA6eSAJknQnCG5MyS3pDmSikskSaOSAj6/fO3mZnQOjo3r/e5ebd/epY3//X9r3Sc/pPr6O1VVVWBqOwAAAAA+MNWmR6mgqqpADQ0PqrGxU1u2HFVLyxmd6swOu55r+3ZGxkzP9p3SwXd2m56IajLZWbmq+XCt9r/9S/UPnLW0LUs5nfrq/jz93RGf8nPdplTpSpMq8qXlBdLacjb7AQAAAJD4FnnO66tFe7X59Er1+GfbHY4uDJ63OwQAAAAAgIVKSzP19NPlam0dUmNjv06eHNGpU6MaGwta2m56ukMLFmRo4UKPampyVVER/jrm1avn6NVXe8I+z5npsXxO8nRG204YLpuWl6vZf3SLRt8/GXW74SbrQuJj+BxA3BoZGdH9998vSXrllVfk8XhsjggApjc0NKTs7NDk1MHBQWVZmIjJbgcP/sdpf775B2f04x+Ft6PqXXdVxHy32WRT5F2sIu/isM45cPBXV/7t7+5VZmWZ2WHFrWPHzio3SZ7uoZ7IklCl0vsWkstMf7ueth7lnDeeWM935oyp8QGJgn43YJ6J/5+4rkKyi7bvOaVpdiqKxvz/+Jm46+tOtjA5mqTMhhNdTWL0I9XSR6oNt+t0uywZTL78Gvm7T2vXyz/Xno99X7t2Pazq6vCSaiGE/r75UuV3Ojt7jvx2B4GkRj8UMA//nxAtuzc9igc1NcWqqpqj7OxslS36grIXfzGs8w8fvjqZcFXVJjU3n1aRd7EyPdNfL14YPKc5ufPCjjlcTqdTVZWrte/AdgUCU28ylQiODbp1bNC8+na3h76W75deqJVWes2rOxWlSp8plvidJpayDV+W3zvHcHlX93kd/9bfWBdQDPA3inhHnwnxjr9RWGGR57w2FP9GTcNetY/OUZcvR2NBR0R1BQIBNTc3SyqS5Ja72CtnJn+niB9cj5qP36l5Vq38RFgboved6zE2rwZIcFwDA7Aa7zP2qKjIiigRlJ0qKrK0alWO2u0OxELjff06/b3/Y3cYSSWV1ouQhAoAACCONTQ0xKCVj8agjZldu9tsW1uf/P7rJ8LmJPDFuWULdS/J9GSFNWBxLV97V8Tnwl5//7b0/W2dEZ1b8IWjkqSbnjkv6bycwYDyg8Mqn+3X59fM1a23sOAXiefcnt/NuMBjoosjQxZGAwAAYK3f/e7PYtqXjrbvaYTHk6VlFdVyOp2Gyk/Xd061hMuXTZboajK5pUOKp2XnLu98FX75s+r59vdVW7tZe/c+pqqqArvDAgAAAADDiryLLe83hyM7K1cF80rU3fu+3aHEpbY+qe6nksbG5Oy9esdjV2uLXK1HTWvLX3Gj/BWVYZ0za+svTGtfkobvqgur/Ey/g7Kyudqy5cFowwIAAABgEpczoFXZXVqVHd184JGREd3/3fslfV5SgQq+8IglG9UAAAAAAGCHRx8t1l+2Rpa4GUh2JKECAABA3KipKVZNzfQJbzb/4Ix+/KO+GEVkrlgs1I3G8KEj8veclqtwvt2hIAKBosiSRV3O6x6Y8LXn0vHrX5zW2Qf+p3ztXVq2LLH+Llwup8rK8lRZma+6usoZ31uQXLq637M7BAAAgJhJxr70yMiQ3j95VCtvuk1paWlR1UXC5cTjSHMq/6E6nXrue9qw4U01NLCYFYhXDt+YLraf1KxZLtVUX/1ZdObsGeW7hm2KDAAAIPZcLmOJlO2QMzuPJFQzSU+/bry199Ax9RtM8mxEbuky5YY5pms0ybRRpZ8Lr32zfwcAAAAAAAAAAACA3UpLM7XIn6lOuwNB1EpKPDMXisKCBRmW1h+PSEIFAAAAIGRsXGdf/oUKv/SYHGnGJ0mvWvmJ6x47cPBXZkaGGBppO6GMGxbK4UqXyztfhV/+rHq+/X01N0d2WyWrZoWyalaGdU7vd38YUVvXamoK7Vb89wNl0uYTkqRZs1ym1C2x8y8AAJjcG2+8IY/HusGM9evXW1Y37FfodWn5iky7w4gLZ/tO6eA7u6NORBXrhMtF3sUq8i6WJAWCAQ0O9WtgoE+9ZzoUCARmOBuXuQrnq/T5/6LGthMq/OKJqPtyzmBA+cFhlc/26/Nr5urWW8xJVNzY2Klf/KJFLS1ndfx4n/z+qV9jf8WN8ldUhlX/rK2/CKs8/VDEWnrfoHq/+0MtWzZfP63//FU/a2j4rU1RAQAA2KOsLE9NTT0KBK3v+3k8WRoZGTJ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",
      "text/plain": [
       "<Figure size 6000x1200 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "feats_to_plot = [15, 16, 17, 10, 9]\n",
    "\n",
    "plot_features(sets, names, feats_to_plot, name = \"core_5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a00ddc9f-5cd1-44cb-b919-422f336a2fa1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35dd8618-75ab-4f05-8c7d-bac3f168e15f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aebcfdaf-31c8-4295-91b9-97cc37b999a7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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